| 1. |
- Liang, Jinpeng, et al.
(författare)
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Robust bus bridging service design under rail transit system disruptions
- 2019
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Ingår i: Transportation Research Part E: Logistics and Transportation Review. - : Elsevier BV. - 1366-5545. ; 132, s. 97-116
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Tidskriftsartikel (refereegranskat)abstract
- This paper focuses on designing robust bus bridging service in response to the rail transit system disruptions. We firstly develop a path-based multi-commodity flow formulation to bus bridging service design. Then its robust counterpart is formulated to incorporate bus travel time uncertainty. The column generation procedure is devised to solve this problem efficiently. At last, we carry out case studies to demonstrate its applicability and promising effects. The results reveal that our approach can significantly reduce the total cost and number of stranded passengers in disruption events. Besides, the rise of bus travel time variation will deteriorate the performance of bus bridging service.
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| 2. |
- Agriesti, Serio Angelo Maria, et al.
(författare)
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Roadworks warning-closure of a lane, the Impact of C-ITS messages
- 2020
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Ingår i: Infrastructures. - : MDPI AG. - 2412-3811. ; 5:3
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Tidskriftsartikel (refereegranskat)abstract
- By now, it is widely acknowledged among stakeholders and academia that infrastructures will have to be composed both by a physical component and a digital one. The deployment of technologies exploiting dedicated short-range communications is viewed as the most cost-effective solution to face the foreseen growth of mobility. Still, little has been done to define the best implementation logic of DSRC. Aim of this paper is to frame the possible impacts arising by the implementation of a cooperative intelligent transport system (C-ITS)-use case: roadworks warning.closure of a lane, and, in order to achieve this result, microsimulations are exploited. The results are intended to support both road operators and car-makers in defining the best operational logics and the possible benefits achievable by presenting the cooperative message at a certain distance for certain market penetrations. Moreover, if the C-ITS message actually entails benefits or simply disrupts the upstream traffic should be assessed in advance, before implementing the system. The obtained results show that the risk of disruption and of reduction in traffic efficiency arises at lower market penetration levels. Nevertheless, a consistent trend in delay reduction is recorded upstream the roadworks, the highest reduction being equal to 8.66%. Moreover, the average speed at the roadworks entrance on the closing lane increases by a difference equal to around 10 km/h, while the average time in the queue at the highest market penetration reduces by 60 s on the open lane and 25 s on the closing one. These presented results reflect the way the traffic shifts from the slow to the fast lane thanks to the C-ITS system and effectively frames both the potentialities and the risks of the system.
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| 3. |
- Basso, Rafael, 1979, et al.
(författare)
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Dynamic Stochastic Electric Vehicle Routing with Safe Reinforcement Learning
- 2022
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Ingår i: Transportation Research Part E: Logistics and Transportation Review. - : Elsevier BV. - 1366-5545. ; 157:157
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Tidskriftsartikel (refereegranskat)abstract
- Dynamic routing of electric commercial vehicles can be a challenging problem since besides the uncertainty of energy consumption there are also random customer requests. This paper introduces the Dynamic Stochastic Electric Vehicle Routing Problem (DS-EVRP). A Safe Reinforcement Learning method is proposed for solving the problem. The objective is to minimize expected energy consumption in a safe way, which means also minimizing the risk of battery depletion while en route by planning charging whenever necessary. The key idea is to learn offline about the stochastic customer requests and energy consumption using Monte Carlo simulations, to be able to plan the route predictively and safely online. The method is evaluated using simulations based on energy consumption data from a realistic traffic model for the city of Luxembourg and a high-fidelity vehicle model. The results indicate that it is possible to save energy at the same time maintaining reliability by planning the routes and charging in an anticipative way. The proposed method has the potential to improve transport operations with electric commercial vehicles capitalizing on their environmental benefits
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| 4. |
- Bie, Yiming, et al.
(författare)
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Dynamic headway control for high-frequency bus line based on speed guidance and intersection signal adjustment
- 2020
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Ingår i: Computer-Aided Civil and Infrastructure Engineering. - : Wiley. - 1093-9687 .- 1467-8667. ; 35:1, s. 4-25
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Tidskriftsartikel (refereegranskat)abstract
- Computer-Aided Civil and Infrastructure Engineering To prevent bus bunching, a dynamic headway control method in the V2I (vehicle to infrastructure) environment for a high-frequency route with bus lane is developed. Bus operating speed guidance on the mid-blocks and intersection signal adjustment are two main strategies in the proposed method. A forecasting model of bus travel time under the dynamic control method is developed. The objective function is set up by taking into account differences between actual bus headways and dispatching headways, and the scaling ratios of intersection cycle lengths. The optimization model is solved using genetic algorithm. The proposed method is applied to a real bus route in Meihekou city, China, and compared with the current control plan as well as holding strategy. Results show that the proposed method can reduce bus headway deviations in all investigating periods; negative impacts on cars can be limited by setting reasonable values for the parameters.
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| 5. |
- Bie, Yiming, et al.
(författare)
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Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption
- 2021
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Ingår i: Computer-Aided Civil and Infrastructure Engineering. - : Wiley. - 1093-9687 .- 1467-8667. ; 36:12, s. 1530-1548
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Tidskriftsartikel (refereegranskat)abstract
- This paper develops a vehicle scheduling method for the electric bus (EB) route considering stochastic volatilities in trip travel time and energy consumption. First, a model for estimating the trip energy consumption is proposed based on field-collected data, and the probability distribution function of trip energy consumption considering the stochastic volatility is determined. Second, we propose the charging strategy to recharge buses during their idle times. The impacts of stochastic volatilities on the departure time, the idle time, the battery state of charge, and the energy consumption of each trip are analyzed. Third, an optimization model is built with the objectives of minimizing the expectation of delays in trip departure times, the summation of energy consumption expectations, and bus procurement costs. Finally, a real bus route is taken as an example to validate the proposed method. Results show that reasonable idle times can be generated by optimizing the scheduling plan, and it is helpful to stop the accumulation of stochastic volatilities. Collaboratively optimizing vehicle scheduling and charging plans can reduce the EB fleet and delay times while meeting the route operation needs.
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| 6. |
- Cao, Danni, et al.
(författare)
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A Platoon Regulation Algorithm to Improve the Traffic Performance of Highway Work Zones
- 2021
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Ingår i: Computer-Aided Civil and Infrastructure Engineering. - : Wiley. - 1093-9687 .- 1467-8667. ; 36:7, s. 941-956
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a cooperative traffic control strategy to increase the capacity of non-recurrent bottlenecks such as work zones by making full use of the spatial resources upstream of work zones. The upstream area is divided into two zones: the regulation area and the merging area. The basic logic is that a large gap is more efficient in accommodating merging vehicles than several small and scattered gaps with the same total length. In the regulation area, a non-linear programming model is developed to balance both traffic capacity improvements and safety risks. A two-step solving algorithm is proposed for finding optimal solutions. In the merging area, the sorting algorithm is used to design lane changing trajectories based on the regulated platoons. A case study is conducted, and the results indicate that the proposed model is able to significantly improve work zone capacity with minor disturbances to the traffic.
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| 7. |
- Cao, Danni, et al.
(författare)
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Quantification of the impact of traffic incidents on speed reduction: A causal inference based approach
- 2021
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 157
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Tidskriftsartikel (refereegranskat)abstract
- This paper designs a systemic framework to quantify speed reduction induced by traffic incidents using a causal inference framework. The results can provide a reference to traffic managers for evaluating incident severities, thus take proper control measures after the incident in order not to underestimate or overestimate the negative impact. A two-phase scheme is proposed, including impacted region determination and speed reduction quantification. We first propose a Frame Region (FR) method, based on the shockwave propagation, to determine the spatiotemporal impacted region (SIR) using speed map. It is worth-noting that we design a statistical experiment to prove the rationality of congestion threshold selection. Secondly, we introduce a causal inference method for identifying the matched freeway segments. The traffic condition of finally matched freeway segments can be served as non-incident traffic condition of the incident occurred location, which contributes to quantifying the incident impact on speed reduction. We further demonstrate the proposed method in a case study by taking advantage of an incident record and related real freeway speed data in China. An interesting observation is that, along with the freeway segments away from the incident location, the congestion duration time of different freeway segments firstly rises and then decreases. The case study also illustrates the impact of incident on speed lasts almost 3 h and the congestion caused by the incident spreads 11 km, while the average causal effect of incident on all the impacted freeway segments is 42.3 km/h.
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| 8. |
- Cao, Qi, et al.
(författare)
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Jointly estimating the most likely driving paths and destination locations with incomplete vehicular trajectory data
- 2023
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Ingår i: Transportation Research, Part C: Emerging Technologies. - 0968-090X. ; 155
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Tidskriftsartikel (refereegranskat)abstract
- With an ever-increasing deployment density of probe and fixed sensors, massive vehicular trajectory data is available and show a promising foundation to improve the observability of dynamic traffic demand pattern. However, due to technical and privacy issues, the raw trajectories are not always complete and the paths and destinations between discontinuous trajectory nodes are usually missing. This paper proposes a probabilistic method to jointly reconstruct the missing driving path and destination location of vehicles with incomplete trajectory data. One problem-specific HMM-structured model incorporating spatial and temporal analysis (ST-HMM) is constructed to define the matching probability between observed data and possible movement. Two algorithms, namely candidate set generation and best-match search algorithms, are developed to seek the most possible one as matching result. It can implement end-to-end processing from incomplete trajectory data to complete and connective paths and destinations for the target vehicle. The proposed method is tested based on field-test data and city-wide road network. Compared with two benchmark methods, the proposed method improved the matching accuracy in terms of both path identification and destination inference. Additionally, sensitivity analyses on the size of training dataset and candidate set were performed. We believe that experiment results of these sensitivity analyses can help to provide guidance on data sensing and candidate generation.
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| 9. |
- Chen, Jingxu, et al.
(författare)
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A modelling framework of drone deployment for monitoring air pollution from ships
- 2019
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Ingår i: Smart Innovation, Systems and Technologies. - Cham : Springer International Publishing. - 2190-3026 .- 2190-3018. ; 98, s. 281-288
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Konferensbidrag (refereegranskat)abstract
- Sulphur oxide (SOx) emissions impose a serious health threat to the residents and a substantial cost to the local environment. In many countries and regions, ocean-going vessels are mandated to use low-sulphur fuel when docking at emission control areas. Recently, drones have been identified as an efficient way to detect non-compliance of ships, as they offer the advantage of covering a wide range of surveillance areas. To date, the managerial perspective of the deployment of a fleet of drones to inspect air pollution from ships has not been addressed yet. In this paper, we propose a modelling framework of drone deployment. It contains three components: drone scheduling at the operational level, drone assignment at the tactical level and drone base station location at the strategic level.
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| 10. |
- Chen, Xi, et al.
(författare)
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Customized bus route design with pickup and delivery and time windows: Model, case study and comparative analysis
- 2021
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Ingår i: Expert Systems with Applications. - : Elsevier BV. - 0957-4174. ; 168
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Tidskriftsartikel (refereegranskat)abstract
- The customized bus (CB) is an emerging type of public transportation system, which not only provides a flexible and reliable demand-responsive service, but also reduces the usage of private car to alleviate traffic congestion in metropolitan cities. The customized bus route design problem (CBRDP) is a crucial procedure in the CB service system designing. In this work, we develop a new type of problem scenario: Multi-Trip Multi-Pickup and Delivery Problem with Time Windows, to describe CBRDP by simultaneously optimizing the operating cost and passenger profit, where excess travel time is introduced to estimate passenger extra cost compared with taxi service, and each vehicle is allowed to perform multiple trips for operational cost savings. To solve this problem, a constructive two-stage heuristic algorithm is presented to obtain the Pareto solution. Taking a benchmark problem and Beijing commuting corridor as case studies, we calculate and compare the monetary and travel costs of CB with other travel modes, and quantitatively confirm that the CB can be a cost-effective choice for passengers.
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